Robust iterative learning contouring controller with disturbance observer for machine tool feed drives

In feed drive systems, particularly machine tools, a contour error is more significant than the individual axial tracking errors from the view point of enhancing precision in manufacturing and production systems. The contour error must be within the permissible tolerance of given products. In machining complex or sharp-corner products, large contour errors occur mainly owing to discontinuous trajectories and the existence of nonlinear uncertainties. Therefore, it is indispensable to design robust controllers that can enhance the tracking ability of feed drive systems. In this study, an iterative learning contouring controller consisting of a classical Proportional-Derivative (PD) controller and disturbance observer is proposed. The proposed controller was evaluated experimentally by using a typical sharp-corner trajectory, and its performance was compared with that of conventional controllers. The results revealed that the maximum contour error can be reduced by about 37% on average. •Iterative learning contouring control for feed drive systems is proposed.•Disturbance observer enhances robustness over iteratively varying disturbances.•Contouring controller leads to faster convergence than tracking controller.•The proposed controller allows continuous tracking of high curvatures without stops.•The maximum contour error is reduced by about 37 % over conventional methods.